Coupling simulation and experiment: The bimodal strategy in integrative systems biology

Area of Science:

• Integrative Systems Biology
• Philosophy of Science
• Computational Biology

Background:

• Computational methods are increasingly used in biology, presenting new ways to manage complexity.
• Philosophical exploration of these novel methodological strategies is emerging.
• Integrative systems biology develops unique epistemic and cognitive approaches for complex problem-solving.

Purpose of the Study:

• To enrich the understanding of methodology in integrative systems biology.
• To illustrate novel strategies for managing complexity through a case study.
• To compare bimodal and unimodal modeling strategies in systems biology research.

Main Methods:

• Ethnographic investigation of two systems biology research laboratories.
• Case study of a bimodal researcher integrating wet-lab experimentation with simulation modeling.
• Analysis of how coupled experiment and simulation aids model building, validation, and error localization.

Main Results:

• The bimodal approach, combining experiment and simulation, enabled effective model construction and validation.
• This integrated method allowed for triangulation and localization of errors and uncertainties in biological models.
• Contrasted with unimodal strategies, the bimodal approach offers distinct advantages in managing biological complexity.

Conclusions:

• The coupling of wet-lab experimentation and simulation modeling represents a powerful methodology in systems biology.
• This bimodal strategy offers a robust way to build, validate, and refine models of complex biological systems.
• Distinct methodological approaches exist in systems biology, each with unique affordances for investigating complexity.